This adoption of cooperative systems in so many fields has been paralleled by a renewed interest among researchers in the social and behavioral sciences in the mechanics of cooperation. Perhaps humankind might not be so inherently selfish after all. Through the work of hundreds of scientists, we have begun to see mounting evidence in psychology, organizational sociology, political science, experimental economics, and elsewhere that people are in fact more cooperative and selfless, or at least behave far less selfishly, than most economists and others previously assumed. This isn’t just theory; dozens of field studies have identified cooperative systems, often more stable and effective than equivalent incentive-based ones. Even in the study of human biology, evolutionary biologists and psychologists are now finding neural and possibly genetic evidence of a human predisposition to cooperate.

…

In the next few chapters I will look at the intellectual arc of work in various fields over the past fifty years in several core disciplines concerned with human action and motivation. We will look broadly, but also dive more deeply into the role of cooperation in social relations: the effects of empathy and solidarity, our drive to do what is right and fair, and our desire to conform to the normal. I will draw from such diverse fields as evolutionary biology, experimental economics, psychology, organizational sociology, and neuroscience. I’ll also draw from the real world, with examples ranging from the band Radiohead’s online pricing (or non-pricing) structure to the success of the Obama campaign and case studies of companies like Toyota and Google; from the harsh realities of a group of lobster fishermen to the strides being made by companies simultaneously pursuing social justice and profit.

…

Later in life, we usually develop more complex notions of what is fair. Other facts enter into the equation, such as relative need, luck, and talent. We come to accept that some people are better off than others, and that’s just how it is. And yet we still care about fairness in one way or another. What, then, might we be caring about when we feel that we care about fairness?
In looking through the experimental economics and social psychology literature, it seems that when we care about “fairness” we really care about three distinct things: fairness of outcomes, fairness of intentions, and fairness of processes. With regard to outcomes, we care about how much each of us gets out of an interaction relative to others, given the generally understood norms. For intentions, we particularly care when the outcomes are not “fair” given generally understood conventions for the situation, whether the unfair outcome was intentionally brought about or not.

I keep a photograph of one of those farm stands in my office for inspiration.
16
Mugs
At some point during the Vancouver year, the economist Alvin Roth, who was then deeply involved with experimental methods, organized a conference at the University of Pittsburgh. The goal was to present the first drafts of papers that would later be published in a small book called Laboratory Experimentation in Economics: Six Points of View. The contributors were major figures in the experimental economics community including Al, Vernon Smith, and Charlie Plott. Danny and I represented the new behavioral wing of the experimental economics community.
For Danny and me, the most interesting discussion was about my beloved endowment effect. Both Vernon and Charlie claimed we didn’t have convincing empirical evidence for this phenomenon. The evidence I had presented was based on a paper written by Jack Knetsch along with an Australian collaborator, John Sinden.

…

The problem with a slow hunch is you have no way to know whether it will lead to a dead end. I felt like I had arrived on the shores of a new world with no map, no idea where I should be looking, and no idea whether I would find anything of value.
Kahneman and Tversky ran experiments, so it was natural to think that I should be running experiments, too. I reached out to the two founders of the then nascent field called experimental economics, Charlie Plott at Caltech and Vernon Smith, then at the University of Arizona. Economists traditionally have used historical data to test hypotheses. Smith and Plott were practitioners of and proselytizers for the idea that one could test economic ideas in the laboratory. I first took a trip down to Tucson to visit Smith.
Smith’s research agenda was, at least at that time, different from the one I was imagining for myself.

…

This assertion, unsupported by any evidence, was firmly believed, even in spite of the fact that nothing in the theory or practice of economics suggested that economics only applies to large-stakes problems. Economic theory should work just as well for purchases of popcorn as for automobiles.
Two Caltech economists provided some early evidence against this line of attack: David Grether and Charlie Plott, one of my experimental economics tutors. Grether and Plott had come across research conducted by two of my psychology mentors, Sarah Lichtenstein and Paul Slovic. Lichtenstein and Slovic had discovered “preference reversals,” a phenomenon that proved disconcerting to economists. In brief, subjects were induced to say that they preferred choice A to choice B . . . and also that they preferred B to A.
This finding upset a theoretical foundation essential to any formal economic theory, namely that people have what are called “well-defined preferences,” which simply means that we consistently know what we like.

Thaler, “Toward a Positive Theory of Consumer Choice,” Journal of Economic Behavior and Organization 1 (1980): 39–60. Reprinted in Thaler, Quasi Rational Economics.
19. Richard H. Thaler and H. M. Shefrin, “An Economic Theory of Self-Control,” Journal of Political Economy (April 1981): 392–406.
20. The best description of Chamberlin’s experiment, and of the rise of experimental economics in general, is in Ross M. Miller, Paving Wall Street: Experimental Economics and the Quest for the Perfect Market (New York: John Wiley & Sons, 2002).
21. It’s called the Social Science Faculty, and includes anthropologists, psychologists, political scientists, and legal scholars as well as economists.
CHAPTER 11: BOB SHILLER POINTS OUT THE MOST REMARKABLE ERROR
1. At least, that’s how Thaler remembers it. The account is assembled from his recollections as well as those of Shefrin and Kahneman.

He left the idea alone for a while after that, only to revive it during a stint as a visiting professor at Caltech in the mid-1970s. The science and engineering hotbed had created an Economics Department of sorts,21 and Smith’s former Purdue colleague Charles Plott was one of its early hires. Together, they began to see the laboratory not just as an educational device but as a serious means of verifying economic theories. Smith and Plott hatched test after test, developing an experimental-economics ethos that has lived on at Caltech and a few other campuses, the most important element being that participants must compete for real monetary rewards. These weren’t the questionnaires and what-if scenarios used by other social scientists, but actual markets—albeit artificial ones populated almost exclusively by college students.
The study of finance was replete with experimental possibilities.

Many of the papers he has published over the years have been collected in two volumes: Smith, Papers in Experimental Economics (Cambridge: Cambridge University Press, 1991); and Smith, Bargaining and Market Behavior (Cambridge: Cambridge University Press, 2000).
The key paper is Kenneth J. Arrow and Gerard Debreu, “Existence of an Equilibrium for a Competitive Economy,” Econometrica 22 (1954): 265–90. See also Arrow, “The Role of Securities in the Optimal Allocation of Risk-Bearing,” Review of Economic Studies 31 (1964): 91–96. (Oddly, this essay was first published in French in 1953, and was only published in English eleven years later, even though it was written in English to begin with.) See also Debreu, Theory of Value (New York: Wiley, 1959).
Vernon L. Smith’s Nobel lecture offers an excellent survey of not just experimental economics but also of current thinking about what efficient market exchange requires.

…

Markets, we know, foster selfishness and greed, not trust and fairness. But even if you find the history unconvincing, there is this to consider: in the late 1990s, under the supervision of Bowles, twelve field researchers—including eleven anthropologists and one economist—went into fifteen “small-scale” societies (essentially small tribes that were, to varying degrees, self-contained) and got people to play the kinds of games in which experimental economics specializes. The societies included three that depended on foraging for survival, six that used slash-and-burn techniques, four nomadic herding groups, and two small agricultural societies. The three games the people were asked to play were the three standards of behavioral economics: the ultimatum game (which you just read about), the public-goods game (in which if everyone contributes, everyone goes away significantly better off, while if only a few people contribute, then the others can free ride off their effort), and the dictator game, which is similar to the ultimatum game except that the responder can’t say no to the proposer’s offer.

…

In practice, what would this mean? The flow of information within the organization shouldn’t be dictated by management charts. Specifically, companies can use methods of aggregating collective wisdom—like, most obviously, internal decision markets—when trying to come up with reasonable forecasts of the future and even, potentially, when trying to evaluate the probability of possible strategies. Despite the evidence from experimental economics and places such as the IEM, companies have been strangely hesitant to use internal markets. But the few examples that we have suggest that they could be very useful. In the late 1990s, for instance, Hewlett-Packard experimented with artificial markets—set up by the economists Charles R. Plott and Kay-Yut Chen—to forecast printer sales. (Essentially, Hewlett-Packard employees, who were drawn from different parts of the company to ensure the diversity of the market, bought and sold shares depending on what they thought sales in the next month or the next quarter would be.)

This is because people have natural intuitive mechanisms—mind modules that serve them
well in daily interchanges—enabling them to “read” situations and the
intentions and likely reactions of others without deep, tutored, cognitive analysis. This fact has been established by “experiments” performed
by a large school of economics researchers (the bibliography of which
contains 1500 entries [197]) in the ﬁelds of “experimental economics”
[389].
These experimental approaches to economics, started in the midtwentieth century, were developed to examine propositions implied by
economic theories of markets. An untested theory is simply a hypothesis,
and science seeks to expand our knowledge of things by a process of testing hypotheses. In contrast, much of traditional economic theory can be
called, appropriately, “ecclesiastical theory”; it is accepted (or rejected)
on the basis of authority, tradition, or opinion about assumptions, rather
than on the basis of having survived a rigorous falsiﬁcation process
positi ve feedback s
85
that can be replicated.

…

The fact that economic agents can achieve efﬁcient outcomes that are
not part of their intentions was the key principle formulated by Adam
Smith [384], as we already stressed. Indeed, “in many experimental markets, poorly informed, error-prone, and uncomprehending human agents
interact through the trading rules to produce social algorithms which
demonstrably approximate the wealth maximizing outcomes traditionally
thought to require complete information and cognitively rational actors”
[391].
In much of the literature on experimental economics [101, 226, 143],
the rational expectations model has been the main benchmark against
which to check the informational efﬁciency of experimental markets.
The research generally falls into two categories: information dissemination between fully informed agents (“insiders”) and uninformed agents,
and information aggregation among many partially informed agents. The
former experiments investigate the common intuition that market prices
reﬂect insider information, hence uninformed traders should be able to
infer the true price from the market.

Were the P/E and sales volume figures scanner data, a price consultant would conclude that the “consumers” of corporate earnings have remarkably inelastic demand. This was roughly Graham’s assessment. He believed that most investors made emotional decisions to plunge into or out of the market and didn’t care much about the price.
There has been much experimental work on the psychology of market prices. Colin Camerer has used Caltech’s Laboratory for Experimental Economics and Political Science to create super-simplified stock markets. The lab is the creation of Charles Plott, one of the economists who replicated preference reversal. It consists of a grid of cubicles, each with a computer. Every keystroke or mouse action is recorded and archived by software. At the end of an experiment, the researcher can play back everything that happened like a TiVo’d movie.

Under this construct, people gave on average about $4, or 20 percent of their money.
The message couldn’t have been much clearer: human beings indeed seemed to be hardwired for altruism. Not only was this conclusion uplifting—at the very least, it seemed to indicate that Kitty Genovese’s neighbors were nothing but a nasty anomaly—but it rocked the very foundation of traditional economics. “Over the past decade,” Foundations of Human Sociality claimed, “research in experimental economics has emphatically falsified the textbook representation of Homo economicus.”
Non-economists could be forgiven if they felt like crowing with satisfaction. Homo economicus, that hyper-rational, self-interested creature that dismal scientists had embraced since the beginning of time, was dead (if he ever really existed). Hallelujah!
If this new paradigm—Homo altruisticus?—was bad news for traditional economists, it looked good to nearly everyone else.

…

After all, some of the nation’s most brilliant academic researchers had scientifically established that human beings are altruistic by their very nature. Perhaps this altruism was just an ancient evolutionary leftover, like that second kidney. But who cared why it existed? The United States would lead the way, a light unto the nations, relying proudly on our innate altruism to procure enough donated kidneys to save tens of thousands of lives every year.
The Ultimatum and Dictator games inspired a boom in experimental economics, which in turn inspired a new subfield called behavioral economics. A blend of traditional economics and psychology, it sought to capture the elusive and often puzzling human motivations Gary Becker had been thinking about for decades.
With their experiments, behavioral economists continued to sully the reputation of Homo economicus. He was starting to look less self-interested every day—and if you had a problem with that conclusion, well, just look at the latest lab results on altruism, cooperation, and fairness.

…

Out of loyalty, List presented the offer to his dean, expecting UCF to at least match the offer.
“For $63,000,” he was told, “we think we can replace you.”
His stay at Arizona was brief, for he was soon recruited by the University of Maryland. While teaching there, he also served on the President’s Council of Economic Advisors; List was the lone economist on a forty-two-person U.S. delegation to India to help negotiate the Kyoto Protocol.
He was by now firmly at the center of experimental economics, a field that had never been hotter. In 2002, the Nobel Prize for economics was shared by Vernon Smith and Daniel Kahneman, a psychologist whose research on decision-making laid the groundwork for behavioral economics. These men and others of their generation had built a canon of research that fundamentally challenged the status quo of classical economics, and List was following firmly in their footsteps, running variants of Dictator and other behavioralist lab games.

Because information in a decentralized market economy is "asymmetric"—"different people know different things," which in turn can lead to "thin or non-existent markets" (2001, 488-89). What Hayek views as positive, Stiglitz sees as negative.
Market economists counter Stiglitz by arguing that while imperfect information may indeed be pervasive, the outcome of the imperfect competitive market system acts "as if' it is perfectly competitive.
For example, experimental economics seems to confirm this "as if'
approach. Vernon L. Smith, Nobel laureate from George Mason University and founder of experimental economics, ran an experiment to test the Chamberlin-Robinson "imperfect competition" model. Recall from chapter 5 that this model suggested that a small number of sellers (or buyers) creates an imperfect form of competition, causing prices to rise, and output to fall. The imperfect monopolistic model was therefore inefficient, and gave support to government antitrust actions to break up big businesses and force more competition into the industry.

Yet there’s plenty of material for such an education because lots of social scientists have studied, from one angle or another, the questions of how middlemen provide value and profit from their roles between buyers and sellers. For example, economic theory has much to say about transaction-cost economics, two-sided markets, and intermediaries’ ability to reduce information asymmetries between buyers and sellers. In particular, game theory informs our understanding of repeated interactions, reputations, shirking and cheating, and third-party enforcement. Social psychology and experimental economics show how acting on behalf of others affects people’s behavior and impressions. And sociology offers insights into the ways the structures of social networks create opportunities for middlemen. This book reports on fascinating research from these and other fields, revealing the ways in which the scientific findings illuminate and reinforce the lessons that top middlemen have picked up on the job.

…

The number rises to $10,000 for Gold, $25,000 for Platinum, and an astounding $150,000 per month for Titanium.
17.You must also get consistently high feedback scores from your buyers: fall anywhere below 98 percent positive feedback, and you lose your PowerSeller status.
18.Interview with Ann Whitley Wood, September 24, 2013.
19.Along the same lines, a recent article pointed out that large players also dominate the Prosper Marketplace (where two-thirds of the lenders are hedge funds and other large institutions) and that nearly half of the hosts on Airbnb had at least three listings on the site, suggesting these hosts weren’t just renting out a spare bedroom. See William Alden, “The Business Tycoons of Airbnb,” New York Times Magazine, November 25, 2014.
20.Paul Resnick, Richard Zeckhauser, John Swanson, and Kate Lockwood, “The Value of Reputation on eBay: A Controlled Experiment,” Experimental Economics 9, no. 2 (2006): 79–101.
21.Nira Yacouel and Aliza Fleischer, “The Role of Cybermediaries in Reputation Building and Price Premiums in the Online Hotel Market,” Journal of Travel Research 51, no. 2 (2012): 219–26.
22.Michael Anderson and Jeremy Magruder, “Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database,” The Economic Journal 122, no. 563 (September 2012): 957–89.
23.Michael Luca, “Reviews, Reputation, and Revenue: The Case of Yelp.com,” Harvard Business School Working Paper, No. 12–016.
24.Carl Shapiro, “Premiums for High Quality Products as Returns to Reputation,” The Quarterly Journal of Economics (November 1983): 659–79.
25.Investing in a storefront is one of several ways sellers can elicit trust among buyers.

A paper on war games was merely a half-hearted effort, designed to justify his employment at RAND and to be hastily drafted before he returned to Cambridge at the beginning of September.14
But Nash and Milnor did collaborate on one project, an experiment on bargaining involving hired subjects, that was to become, unexpectedly, a much-cited classic.15 The experiment, designed with two researchers from the University of Michigan who were also at RAND for the summer, anticipated by several decades the now-thriving field of experimental economics.
The RAND experiments grew more or less directly out of the habit of playing games that the mathematicians indulged in their spare time. Inventing new games and trying them out, always with the inventors as subjects, had been a popular pastime at Princeton. Many of the players had, like Nash, only recently outgrown boyhood passions for chemistry and electricity experiments. The idea of recording the play to see whether people played the way the theory predicted was already a bit of a tradition at RAND, inaugurated by the famous Prisoner’s Dilemma experiment.

.
[>] “signaling mechanism”: On the economics job market, and on the mechanism we built to allow candidates to signal particular interest, see Peter Coles, John H. Cawley, Phillip B. Levine, Muriel Niederle, Alvin E. Roth, and John J. Siegfried, “The Job Market for New Economists: A Market Design Perspective,” Journal of Economic Perspectives 24, no. 4 (Fall 2010): 187–206.
[>] The experiment allowed: Soohyung Lee and Muriel Niederle, “Propose with a Rose? Signaling in Internet Dating Markets,” Experimental Economics, forthcoming.
[>] And the effect of a rose: This turns out to echo the effect of signals that we observe in the economics job market when we use the relative prestige of the university from which the applicant is graduating and the one to which he or she is applying as a measure of desirability. This turns out to echo the effect of signals that we observe in the economics job market when we use the relative prestige of the university from which the applicant is graduating and the one to which he or she is applying as a measure of desirability.
[>] impressive genetic resources: For signals of desirability in biology, see Amotz Zahavi, The Handicap Principle: A Missing Piece of Darwin’s Puzzle (Oxford: Oxford University Press, 1997).
[>] one of the oldest: Herodotus writes in The Histories (1.196) that the Babylonians used to sell marriageable girls, once a year, in an auction in which each of the most beautiful girls would be sold for a high price to the highest bidder among the wealthy men, and each of the others would go to the bidder who demanded the smallest dowry.

Innovative Abstract Visualizations
Experimental markets are a remarkable laboratory technique that allows
investigation of markets that would not be possible by observing real
financial markets from a distance.Vernon Smith shared the 2002 Nobel
Prize in economics for pioneering experimental economics.15 Vernon
is also the hands-down winner of the “Nobel laureate who looks most
like Willie Nelson” award.
Smith’s colleagues can create (and have created) markets that have
any degree of transparency they want. They have created automated
and semi-automated systems that may give us insight into how we will
approach markets technologically in the future. Charles Plott, Smith’s
sometime collaborator at Caltech’s Experimental Economics Laboratory,
has developed a novel visualization that allows participants to look deeply
into the workings of the market. His invention, called Jaws, can be seen in
living color and full animation at http://eeps.caltech.edu/mov/jaws.html.

…

There is a huge collection of past and current HCIL work at the lab’s site:
www.cs.umd.edu/hcil/.
14. The tree map is still enormously useful for its original purpose—tracking down
those files that suddenly take over your disk. A free utility along these lines is Sequoia
View, from the computer science department at Eindhove Technical University in the
Netherlands (www.win.tue.nl/sequoiaview/).
15. For more on this remarkable story, see Paving Wall Street: Experimental Economics and the
Quest for the Perfect Market by Ross Miller ( John Wiley & Sons, 2002).
16. See “Delving Deeper” by David Leinweber, Bloomberg Wealth Manager, October 2003.
17. The Harvard Business School e-Information project at www.people.hbs.edu/ptufano/einfo/ has a nice online collection of these studies.
18. Ser-Huang Poon and Clive Granger, “Practical Issues in Forecasting Volatility,”
Financial Analysts Journal 61, no. 1 (2005): 45–55.
19.

WHAT CAN WE LEARN FROM THE MARRIAGE OF ECONOMICS AND NEUROSCIENCE?
Today, this multidisciplinary field—which brings together economics, neuroscience, psychology, philosophy, sociology, and physics—is offering new empirical and theoretical insights on how emotions and rationality interdependently sha(r)p(en) our decisions. Among the most striking examples are a couple of neuroscientific studies of a familiar experimental economic setting, the Ultimatum Game (UG). The first of these was conducted by scientists at Princeton University in 2003.8 Alan Sanfey, Jonathan Cohen, and colleagues used functional magnetic resonance imaging (fMRI)9 in order to estimate the brain activity that occurs when people decide to accept (or not) an unfair share of money in the UG.10 From a purely rational view, whether a proposition is unfair or not should not make any difference to their decision—they would get more money by accepting than by rejecting it.

…

Camerer, California Institute of Technology
Colin Camerer is the Rea and Lela Axline Professor of Business Economics at the California Institute of Technology (located in Pasadena, California), where he teaches cognitive psychology and economics. He earned an MBA in finance and a PhD in decision theory from the University of Chicago Graduate School of Business. Before coming to Caltech in 1994, Professor Camerer worked at the Kellogg, Wharton, and University of Chicago business schools. He studies both behavioral and experimental economics. His most recent books include Behavioral Game Theory (Princeton University Press, 2003), Foundations of Human Sociality, with fourteen co-authors (Oxford University Press, 2004), and Advances in Behavioral Economics, co-edited with George Loewenstein and Matthew Rabin (Princeton University Press, 2004).
Neil Doherty, The Wharton School
Neil Doherty is the Frederick H. Ecker Professor of Insurance and Risk Management and past chair of the Department of Insurance and Risk Management at The Wharton School of the University of Pennsylvania.

The school extends this approach to the study of economic institutions and organizations – for example, how best to organize a firm or how to design financial regulation. The school thus has a fundamental affinity, and some overlap in membership, with the Institutionalist school.
The Behaviouralist school is the youngest of the schools of economics that we have so far examined, but it is older than most people think. The school has recently come to prominence through the fields of behavioural finance and experimental economics. But it has its origins in the 1940s and the 1950s, especially in the works of Herbert Simon (1916–2001), the 1978 Nobel economics laureate.*
Limits to human rationality and the need for individual and social rules
Simon’s central concept is bounded rationality. He criticizes the Neoclassical school for assuming that people possess unlimited capabilities to process information, or God-like rationality (he calls it ‘Olympian rationality’).

…

The Behaviouralist school’s attempt to understand human society from individuals up – actually from a place ‘lower’ than that, that is, from our thinking process up – is both its strength and its weakness. Focusing too much at this ‘micro’ level, the school often loses sight of the bigger economic system. This does not have to be; after all, Simon wrote a lot about the economic system. But most members of the school have focused too much on individuals – especially those economists who are engaged in experimental economics (trying to establish whether people are rational and selfish through controlled experiments) or neuroeconomics (trying to establish links between brain activities and particular types of behaviour). It also needs to be added that, given its focus on human cognition and psychology, the Behaviouralist school has few things to say about issues of technology and macroeconomics.
Concluding Remarks: How to Make Economics Better
Preserving intellectual diversity and encouraging cross-fertilization of ideas
Recognizing that there are different approaches to economics is not enough.

pages: 403words: 111,119

Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist
by
Kate Raworth

Other goods, such as wine and Super Bowl tickets, are held “for use,” to be consumed or otherwise enjoyed. Your leisure time and the standard of living that your income supports are also not intended for sale or exchange.
Knetsch, Thaler, and I set out to design an experiment that would highlight the contrast between goods that are held for use and for exchange. We borrowed one aspect of the design of our experiment from Vernon Smith, the founder of experimental economics, with whom I would share a Nobel Prize many years later. In this method, a limited number of tokens are distributed to the participants in a “market.” Any participants who own a token at the end Bon s A end Bon of the experiment can redeem it for cash. The redemption values differ for different individuals, to represent the fact that the goods traded in markets are more valuable to some people than to others.

…

“Each of our executives is loss averse in his or her domain. That’s perfectly natural, but the result is that the organization is not taking enough risk.”
Keeping Score
Except for the very poor, for whom income coincides with survival, the main motivators of money-seeking are not necessarily economic. For the billionaire looking for the extra billion, and indeed for the participant in an experimental economics project looking for the extra dollar, money is a proxy for points on a scale of self-regard and achievement. These rewards and punishments, promises and threats, are all in our heads. We carefully keep score of them. They shape o C Th5ur preferences and motivate our actions, like the incentives provided in the social environment. As a result, we refuse to cut losses when doing so would admit failure, we are biased against actions that could lead to regret, and we draw an illusory but sharp distinction between omission and commission, not doing and doing, because the sense of responsibility is greater for one than for the other.

De Moivre first conceived of the bell curve by writing equations on a piece of paper, not, like Quetelet, by measuring the dimensions of soldiers. But Galton conceived of regression to the mean-a powerful concept that makes the bell curve operational in many instances-by studying sweetpeas and generational change in human beings; he came up with the theory after looking at the facts.
Alvin Roth, an expert on experimental economics, has observed that Nicholas Bernoulli conducted the first known psychological experiment more than 250 years ago: he proposed the coin-tossing game between Peter and Paul that guided his uncle Daniel to the discovery of utility.26 Experiments conducted by von Neumann and Morgenstern led them to conclude that the results "are not so good as might be hoped, but their general direction is correct."'-' The progression from experiment to theory has a distinguished and respectable history.

SOURCES
CHAPTER 7: The Combo Special:
The Hybrid Organization
EClass229 still offers unbelievable bargains for designer clothing. Since
our coup with the Zegna suits, we've recommended it to all our friends.
The value of positive feedback on eBay is explained in Paul Resnick,
Richard Zeckhauser, John Swanson, and Kate Lockwood, "The Value of
Reputation on eBay: A Controlled Experiment," Experimental Economics
(forthcoming).
A comprehensive overview of Google's history can be found in John
Battelle's The Search—How Google and Its Rivals Rewrote the Rules of
Business and Transformed Our Culture (New York: Portfolio, 2005).
The story of IBM's decision to give away its software is told by David
Kirkpatrick in "Giving to Get More: IBM Shares Its Secrets," Fortune
(August 22, 2005).
David Cooperrider has written extensively about appreciative inquiry.

Klein, Christian Lambertz, Giancarlo Spagnolo, and Konrad O. Stahl, “The Actual Structure of eBay’s Feedback Mechanism and Early Evidence on the Effects of Recent Changes,” International Journal of Electronic Business 7.3 (2009): 301-20.
177 an 8 percent premium on price: Paul Resnick published these findings with his coauthors Richard Zeckhauser, John Swanson, and Kate Lockwood, in “The Value of Reputation on eBay: A Controlled Experiment,” Experimental Economics 9.2 (2006): 79-101.
179 added a fake quote to composer Maurice Jarre’s Wikipedia page: Shawn Pogatchnik discussed Fitzgerald’s actions in “Student Hoaxes World’s Media on Wikipedia,” MSNBC, May 12, 2009, http://www.msnbc.msn.com/id/30699302 (accessed January 10, 2010).
CHAPTER 7: Looking for the Mouse
185 notes in his book The Success of Open Source: Steven Weber, The Success of Open Source (Cambridge, MA: Harvard University Press, 2005): 272.
188 He got a loan to enter the indulgence-printing business: The British Library discusses Gutenberg’s printing of indulgences in its documentation of Gutenberg’s Bible: http://www.bl.uk/treasures/gutenberg/indulgences.html (accessed January 9, 2010).
188 John Tetzel, the head pardoner for German territories: Tetzel’s place in history was largely secured by Martin Luther’s objections to indulgences in 1517, but his name recently reappeared when the Catholic Church brought back indulgences in 2008; in discussing this change, John Allen references Tetzel’s phrase in the Room for Debate blog, http://roomfordebate.blogs.nytimes.com/2009/02/13/sin-and-its-indulgences (accessed January 7, 2010).
190 As Elizabeth Eisenstein notes in The Printing Press as an Agent of Change: Elizabeth Eisenstein, The Printing Press as an Agent of Change: Communications and Cultural Transformations in Early-Modern Europe (Cambridge, U.K.: Cambridge University Press, 1980).
192 a computer system called PLATO: Elisabeth Van Meer discusses this history in “PLATO: From Computer-Based Education to Corporate Social Responsibility,” Iterations: An Interdisciplinary Journal of Software History (2003): 6-22.
196 “The behavior you’re seeing is the behavior you’ve designed for”: Joshua Porter, “The Behavior You’re Seeing Is the Behavior You’ve Designed For,” Bokardo, July 28, 2009, http://bokardo.com/archives/the-behavior-youve-designed-for (accessed January 10, 2010).
203 One of the most parsimonious examples of this pattern on the web is from JavaRanch: “Be Nice,” JavaRanch, http://faq.javaranch.com/java/BeNice (accessed January 10, 2010).
203 it sometimes upgraded its software every half hour: Nisan Gabbay, “Flickr Case Study: Still About Tech for Exit?”

Reis, and Susan Sprecher, “Online Dating: A Critical Analysis from the Perspective of Psychological Science,” Psychological Science in the Public Interest, January 2012, 13(1): 3–66.
For the tale of Cambry, see David Gelles, “Inside Match.com,” Financial Times, July 29, 2011; this source also has the information on conservatives and liberals and the New Jersey anecdote.
For cognitive biases, see http://en.wikipedia.org/wiki/List_of_cognitive_biases.
For the pointer about experimental economics I am indebted to Amihai Glazer.
In addition to Ken Regan, for another look at using computers to measure the quality of human play, see Matej Guid, “Search and Knowledge for Human and Machine Problem Solving,” doctoral dissertation, University of Ljubljana, 2010, http://eprints.fri.uni-lj.si/1113/1/Matej__Guid.disertacija.pdf. And for a summary of related work, see Matej Guid and Ivan Bratko, “Using Chess Engines to Estimate Human Skill,” Chessbase News, November 11, 2011, http://www.chessbase.com /newsdetail.asp?

Gordon Brown, on taking office as Chancellor in the New Labour government in 1997, immediately gave the Bank of England autonomy in determining interest rates in pursuit of an inflation target. We had come a long way from the euthanasia of the rentier.
Economists do not do fieldwork as anthropologists do, nor do they, on the whole, experiment in a laboratory as natural scientists do. There is a branch called “experimental economics” but it has not changed the nature of the subject to any great extent. But economists do confront published data. The time series of data on income, consumption, investment and so forth are available on an annual or quarterly basis. Economists model them using statistical techniques, like the models Klein built for the US economy. The new classical economists also modeled the data. They, however, did not forecast or judge the quality of their model by the accuracy of their forecasts.

The higher price induces producers to increase their output. If there are unfilled jobs for barrel scrapers, the employers raise the offered wage, people change their jobs in response, and the vacancies get filled. With a price system, unlike under central planning, no central authority needs to know when there is an imbalance of supply and demand.
Evidence that price movements can guide an economy to a stable outcome comes from experimental economics, in research done by Vernon Smith and others.12 An economy is simulated in the laboratory, with experimental subjects, usually undergraduate students, being put in the role of consumers and firms (and to get them to take their decision-making seriously, they are offered cash payments based on the outcomes of their decisions). Provided the experimental market’s rules are well designed, prices quickly settle down at their theoretical equilibrium levels (that is, where supply equals demand), even though no one in the economy knows enough to be able to figure out what those prices should be.

Visible even in young children, our concern for fairness sometimes seems so strong that we might wonder how it is that social systems with great inequality are tolerated. Similarly, the sense of indebtedness (now recognized as universal in human societies) which we experience after having received a gift, serves to prompt reciprocity and prevent freeloading, so sustaining friendship. As the experimental economic games which we discussed showed, there is also evidence that we can feel sufficiently infuriated by unfairness that we are willing to punish, even at some personal cost to ourselves.
Another characteristic which is perhaps important is our tendency to feel a common sense of identity and interdependence with those with whom we share food and other resources as equals. They form the in-group, the ‘us’, with whom we empathize and share a sense of identity.

It is, however, the least radical of the alternative approaches because it does not challenge the central assumption of REH—that booms, busts, and recessions are all caused by various types of market failure and therefore that breakdowns in laissez-faire capitalism could, at least in principle, be prevented by making markets more perfect, for example, by disseminating information or strengthening the regulations against fraud. Partly because of this ideological compatibility, academic economics has been quite willing to embrace the behavioral approach. Indeed, the work on bounded rationality by Herbert Simon, game theory by Vernon Smith, experimental economics by Daniel Kahneman, and asymmetrical information by George Akerloff, Joe Stiglitz, and Michael Spence have all been rewarded with Nobel prizes.
More challenging to orthodox economics is the mathematical work in chaos theory and advanced control engineering, which suggests that most of the mathematical techniques used by precrisis academic economics were simply wrong. Brian Arthur, along with colleagues at the Santa Fe Institute, has spent a lifetime developing the mathematics of nonlinear complex systems and applying them to the self-organizing emergent behavior of economies and markets that involve properties defying the assumptions of standard economics, for example, increasing returns and winner-takes-all positive feedbacks.

He is a coeditor of Econometrica and NAJ Economics, president of the Society for Economic Dynamics, a Fellow of the Econometric Society, and a research associate of the National Bureau for Economic Research. Author with Drew Fudenberg of Learning in Games and editor of several conference volumes, his research interests include the study of intellectual property and endogenous growth in dynamic general equilibrium models; the endogenous formation of preferences, institutions, and social norms; and the application of game theory to experimental economics.
Levine has published in leading journals such as American Economic Review, Econometrica, Review of Economic Studies, Journal of Political Economy, Journal of Economic Theory, Quarterly Journal of Economics, and American Political Science Review.
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Against Intellectual Monopoly
MICHELE BOLDRIN
Washington University in St.

It all happens unconsciously, in our mind, in our body. Right away. We’re not even rational in the sense of being logical and explicitly deductive. We’re fast, intuitive, and emotional.
Economists believe we are Homo economicus—selfish and rational, acting with reason in our own self-interest. But most economic and social interactions deal with fairness, trust, sharing, and long-term relationships. Experimental economics shows us that when we act directly and without hesitation, we’re social and cooperative. Only when we start thinking for some seconds do we choose to be selfish.
Unless we deal with computers. When we play economic games with machine counterparts, we tend to be cold and egoistic. You can even measure the difference in our blood flow in the brain and in the hormones in our bloodstream. We think of machines the way economists think about us—as rational, cold-blooded, and selfish.

Of course they do:
they are farming the government, not merely the pastures, and the
public lands are therefore nowadays overgrazed. But in olden days, such
as the days of open-field agriculture, the land was private or was
regulated when it mattered. And in any case, as the political scientist
Elinor Ostrom has shown repeatedly, people cooperate, too: they do not
always defect from the common good, as assumed by Hardin.108 It is one
of the main findings of experimental economics that people cooperate
much more than the prudence-only model Hardin was using would
imply. Anyone who troubles to examine local regulations or legal cases
in the not-so-wild West, or in English villages in the fourteenth century,
will find stinting enforced.109 Hardin, though an impressive scholar in
some other ways, appears not to have looked into the evidence.
Likewise, if you look into the national and local regulations and
legal cases in thirteenth century England you will find private property
enforced — and never mind the alternative of “preinstitutional ‘natural’
private property” enforced by shame and ostracism that Gintis talks
about.

To be sure, economics has had its place in the it industry for some
years now. hp, for instance, already uses software that simulates markets to optimise the air-conditioning systems in its utility data centres.
And ibm’s Institute for Advanced Commerce has studied the behaviour
of bidding agents, in the hope of designing them in such a way that they
do not engage in endless price wars.
Now hp is reaching even higher, with experimental economics. As
the name implies, researchers in this field set up controlled experiments
with real people and real money to see whether economic theories actually work. Perhaps surprisingly, it seems that they do, as demonstrated
by the work of Vernon Smith of George Mason University in Virginia.
(Mr Smith is considered the founding father of this field and won the
2002 Nobel prize in economics.)
T
Secret agent
hp goes further.

The unbearable lightness of the economy within neoclassicism is only the tip of the iceberg. Let us look more closely at the practical mechanics of orthodox contemporary “economics imperialism.” While gleefully encroaching upon the spheres of interest of other disciplines, orthodox economics has also freely appropriated formalisms and methods from those other disciplines: think of the advent of “experimental economics” or the embrace of magnetic resonance imaging, or attempts to absorb chaos theory or nonstandard analysis or Brownian motion through the Ito calculus. Indeed, if there has been any conceptual constant throughout the history of neoclassical theory since the 1870s, it has been slavish attempts to slake its physics envy through gorging on half-digested imitations of physical models. A social science so promiscuous in its avidity to mimic the tools and techniques of other disciplines has no principled discrimination about what constitutes just and proper argumentation within its own sphere; and this has only become aggravated in the decades since 1980.

Adaptive Markets: Financial Evolution at the Speed of Thought
by
Andrew W. Lo

But
when there are no common risks, the entire population can behave in
exactly the same way, because there’s virtually no chance that all the
individuals will experience a bad outcome at the same time (the one-in-amillion chance of all the independent tribbles getting rained on we
The Adaptive Markets Hypothesis • 203
described before). The difference in adaptation between systematic and
idiosyncratic risk is evolutionarily tremendous, giving rise to entirely
different behaviors. As we saw earlier, nature abhors an undiversified bet.
THE ORIGIN OF RISK AVERSION
Probability matching may seem like foolish behavior in an experimental economics laboratory, but it’s likely to have originated from an environment where that kind of behavior conferred certain survival benefits
that other behaviors did not. Using the mathematical framework that
Tom and I developed, we can identify the specific environments that
gave rise to such behavior. In other words, we can trace the origin of all
sorts of behaviors to their evolutionary roots, rather than simply asserting that people behave in a certain way, as traditional economic theory
often does.